Dissipative iFIR filters for data-driven design

Fuente: arXiv
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Main Authors: Wang, Zixing, Zhang, Yi, Forni, Fulvio
Format: Preprint
Published: 2024
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author Wang, Zixing
Zhang, Yi
Forni, Fulvio
author_facet Wang, Zixing
Zhang, Yi
Forni, Fulvio
contents We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.
format Preprint
id arxiv_https___arxiv_org_abs_2412_00211
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dissipative iFIR filters for data-driven design
Wang, Zixing
Zhang, Yi
Forni, Fulvio
Systems and Control
Robotics
Optimization and Control
We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable with respect to the length of the data and the complexity of the controller. An extension of virtual reference feedback tuning to include disturbance dynamics is also discussed. The proposed data-driven control design is illustrated by a soft gripper impedance control example.
title Dissipative iFIR filters for data-driven design
topic Systems and Control
Robotics
Optimization and Control
url https://arxiv.org/abs/2412.00211